Abstract
Understanding user behavior is an important issue to make any prediction of the resource utilization and the distribution of information in social networks as well as to determine approaches to optimize the networks. Based on the results of surveys, a typical group of users, their behaviors and activities in the online social network Facebook have been analyzed and classified. The results confirm the validity of power laws and small-world properties in various areas of social network systems and will later allow the establishment of useful models for further simulations and investigations in the area of social network mining.
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Vongsingthong, S., Boonkrong, S., Kubek, M., Unger, H. (2015). On the Distributions of User Behaviors in Complex Online Social Networks. In: Unger, H., Meesad, P., Boonkrong, S. (eds) Recent Advances in Information and Communication Technology 2015. Advances in Intelligent Systems and Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-19024-2_24
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DOI: https://doi.org/10.1007/978-3-319-19024-2_24
Publisher Name: Springer, Cham
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